BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -Prescriptive analytics relies on optimization and rules-based techniques for decision making. Optimization techniques such as linear programming, integer programming, and nonlinear programming play an important role in prescriptive analytics, since they enable a set of decisions to be made in an optimal way.

Detailed explanation-2: -The 4 Types of Data Analytics Prescriptive analytics builds upon the three other types of data analytics which describe the present and make predictions about the future. It then uses heuristics, machine learning and rule-based systems to make specific recommendations based on data and probability-weighted projections.

Detailed explanation-3: -The goal of prescriptive analytics linear programming is to optimize a solution. Typically, the first step is to define a model that represents business reality, including all limitations and constraints. A key step in the process is model validation to ensure it reflects business realities.

Detailed explanation-4: -Predictive analytics forecasts potential future outcomes, while prescriptive analytics helps you draw specific recommendations. Predictive and prescriptive analytics are tools for turning descriptive metrics into insights and decisions.